Digital watermarking—a form of steganography—is a process for modifying media content to embed a machine-readable code into the content. The content may be modified such that the embedded code is imperceptible or nearly imperceptible to the user, yet may be detected through an automated detection process. Most commonly, digital watermarking is applied to media such as images, audio signals, and video signals. However, it may also be applied to other types of data, including text documents (e.g., through line, word or character shifting, background texturing, etc.), software, multi-dimensional graphics models, and surface textures of objects.
Digital watermarking systems typically have two primary components: an embedding component (or encoder) that embeds a watermark in media content, and a reading component (or detector) that detects and reads the embedded watermark. The embedding component embeds a watermark by altering data samples of the media content in the spatial, temporal or some other domain (e.g., Fourier, Discrete Cosine or Wavelet transform domains). The reading component analyzes target content to detect whether a watermark is present. In applications where the watermark encodes information (e.g., a plural-bit message), the reader extracts this information from the detected watermark.
The present assignee's work in steganography, data hiding and digital watermarking is reflected, e.g., in U.S. Pat. Nos. 5,862,260, 6,408,082, 6,614,914 and 7,027,614, which are each hereby incorporated by reference. A great many other approaches are familiar to those skilled in the art. The artisan is presumed to be familiar with the full range of literature concerning steganography, data hiding and digital watermarking.
In some cases digital watermarking and other machine-readable indicia (e.g., barcodes, data glyphs, etc.) may be detected from optical scan data, examples of which are disclosed in, e.g., U.S. Pat. Nos. 5,978,773, 6,522,770, 6,681,028, 6,947,571 and 7,174,031, which are each hereby incorporated by reference.
Today's camera phones and other handheld readers present expanded decoding opportunities—and challenges.
One challenge is providing handheld cameras (e.g., in a cell phone or other mobile device) to an army of users, with nearly each user having a different idea on proper focal length for image and video capture.
In some cases a user may want to be close to a marked image or video to, e.g., capture high spatial frequency content (see FIG. 1); but the close positioning often results in a captured image that is slightly out of focus (or blurred)—which may hamper detection of a machine-readable code contained or represented in the image.
Thus, one inventive combination provides a method including: obtaining input data; altering a digital watermark or a digital watermarking process to pre-distort a digital watermark signal, wherein the altering is intended to counteract or compensate for expected distortion enabling machine-based detection of an embedded, pre-distorted digital watermark signal despite the expected distortion; and embedding the pre-distorted digital watermark signal in the input data.
Another inventive combination provides a method including: obtaining a plurality of different models representing different expected distortion associated with a plurality of different data captures, the different data captures each resulting in distortion of a machine-readable signal; indexing the different models; upon receiving a request, selecting a model associated with the request; and providing the selected model.
Still another inventive combination provides a method including: obtaining input data; altering a digital watermark or a digital watermarking process to pre-distort a digital watermark signal, wherein the altering is intended to counteract or compensate for expected distortion due to image capture or an image capture device, the altering enabling machine-based detection of an embedded, pre-distorted digital watermark signal despite the expected distortion; and embedding the pre-distorted digital watermark signal in the input data.
Yet another inventive combination provides a method including: obtaining input data, the input data representing imagery captured with at least an optical lens, the input data comprising test data and a machine-readable signal; evaluating characteristics associated with the test data to determine information regarding lens blurring of the input data associated with the optical lens; adjusting the input data to compensate for or to correct the lens blurring based at least in part on the information; and analyzing the compensated for or corrected input data to obtain the machine-readable signal.
Another inventive combination includes: obtaining input data, the input data representing imagery or video, the input data comprising test data and a machine-readable signal; determining characteristics associated with the test data to determine information regarding signal capture distortion of the input data; based on at least the characteristics, determining an amount of correction or counteracting to be applied to the input data; applying a determined amount of correction or counteracting to the input data; and analyzing corrected or counteracted input data to obtain the machine-readable signal.
Further combinations, aspects, implementations, features, embodiments and advantages will become even more apparent with reference to the following detailed description, the accompanying drawings and claims.